Using high throughput sequencing technology to transform disease surveillance

Overall Objective

Project aim – Utilise high throughput sequencing technology to transform disease surveillance for the Western Australia’s broadacre grains industry. Our model pathogen class for this project will be plant viruses

Project Outcome – A new protocol was developed utilising high-throughput genome sequencing technology for comprehensive and unbiased plant virus detection in a single bulk sample per crop. Therefore, the project aim was achieved.

Project Synopsis

Genome sequencing has revolutionised science by giving researchers access to the code of life. Sequencing technology has been evolving at a breathtaking pace over the past decade. For example, the first human genome cost approximately $1 billion, but now it costs less than $1,000 and continues to get cheaper. The human genome is millions of times larger than the average virus so sequencing virus genomes is even faster and cheaper. More information about the virus can be generated in a much shorter time. This leads to powerful applications being rapidly realised. For example, this technology has been vital during the COVID-19 pandemic to track virus evolution and the emergence of new strains that have important biological differences such as their transmissibility and reaction to vaccines. Now that genome sequencing is no longer cost-prohibitive to agricultural research, its extraordinary power can be leveraged to open up novel avenues for its use. The crop diagnostic and surveillance approach developed in this project marked the first of its kind in Western Australia.

Plant surveillance involves taking a representative sample from an affected crop (commonly 100 leaves), and testing the sample in groups of 2 to 10 (i.e. 10 to 50 sub-samples per crop) for a handful of known endemic viruses to enable estimation of infection rate. Depending on the crop and the viruses that are known to infect it, sometimes multiple different diagnostic platforms such as PCR (molecular) and ELISA (serological) are needed, each with their own unique leaf extraction, costs and technical skill requirements. In many cases, just one virus is detected in the crop and so significant resources are expended testing for the others. Sometimes, due to their specific nature, these tests can miss genetic variants of a species. Furthermore, this process completely misses unexpected or novel viruses that can be pathogenic, neutral, or even synergistic with the crop.

In this project, we collected 100 leaves from 20 grains crops (7 cereal, 7 canola, 6 pulses) during the 2022 and 2023 growing season to develop and validate a completely new way of conducting crop diagnosis and surveillance using cutting edge genome sequencing technology – the Illumina MiSeq (2022 samples) and the Illumina NextSeq (2023 samples). Using this high-throughput sequencing (HTS) method, all 100 samples from each crop were tested in a single test. To validate the new approach, 13 different virus species across the three crop types were tested for using the traditional approach. Turnip yellows virus (TuYV) infection in canola was by far the most common virus detected in the study and is currently a species of current research investigation. The HTS approach detected viruses detected by the traditional approach, and many others that would never have been detected by the traditional approach. Rare strains of TuYV and TuYV satellite RNA with unknown but likely important function were detected. Although reported previously but considered to be rare, cucumber mosaic virus (CMV) was detected in canola raising questions on its impact on canola and the epidemiological importance of canola to CMV infection in lupin and lentil. Lastly, rare or unknown plant viruses with unknown roles were detected in 2 of the samples, and a number of viral sequences from various fungi-infecting viruses were detected in the majority of samples. The HTS approach also proved to be far more efficient and cost-effective than the traditional approach as sub-sampling to confirm infection rate need not be done for viruses that are not present and can be focused on those that are.

Moving forward, this method will exponentially increase the amount of data obtained from field activities in plant virology and provide assumption-free detection of viruses and other microorganisms in grains crops. Genetic variants, new strains, and new viruses can be detected early allowing researchers and industry to make the appropriate adaptations more rapidly. This project also provides a proof-of-concept template for similar surveillance of beneficial and pathogenic species of bacteria, nematodes, phytoplasma and fungi, and beneficial and pest species of arthropods and the symbiotic or pathogenic microorganisms inside them. This greatly facilitates identification of biocontrol agents for some of our most notorious arthropod pests that are increasingly difficult to control with pesticides e.g. nuclear polyhedrosis virus used to control insecticide resistant fall army worm and is now marketed by AgBiTech as Fawligen.